from __future__ import division, print_function
from easydict import EasyDict as edict

import torch
import os
import os.path as osp

ROOT_path   = osp.dirname(osp.dirname(__file__))

config          = edict()
config.useGpu   = torch.cuda.is_available()

network         = edict()
network.backbone= "FPN50"
network.num_anchors = 9
config.network  = network

pasvoc_data     = edict()
pasvoc_data.name= pascal
pasvoc_data.num_classes = 20

dataset         = pasvoc_data
config.dataset  = dataset

train           = edict()
learn           = edict({"lr": 0.001, "momentum": 0.9, "weight_decay":1e-4})
learn.epoch_num = 100
learn.batch_size= 1
learn.saveModelDir  = osp.join(ROOT_path, "exp/train/"+str(config.network.backbone)+"/"+str(dataset.name))
learn.saveEpochGap  = 1
train.learn     = learn
config.train    = train
